Multimedialna platforma wiedzy medycznej Internetowa Księgarnia Medyczna Kalendarium Konferencji
Ginekologia Polska
MENU
Shortcuts Submit an article Author Guidelines Ahead Of Print Reviewers 2023

open access

Vol 90, No 8 (2019)
Review paper
Published online: 2019-08-30
View PDF Download PDF file Supp./Additional Files [1]
Get Citation

Saliva, hair, tears, and other biological materials obtained non-invasively for diagnosis in pregnancy: a literature review

Aleksandra Zygula1, Przemyslaw Kosinski1, Miroslaw Wielgos1
DOI: 10.5603/GP.2019.0082
·
Pubmed: 31482552
·
Ginekol Pol 2019;90(8):475-481.
Affiliations
  1. 1st Chair and Department of Obstetrics and Gynecology, Medical University of Warsaw, Poland

open access

Vol 90, No 8 (2019)
REVIEW PAPERS Obstetrics
Published online: 2019-08-30

Abstract

As medical technology evolves, clinicians are increasingly choosing relatively painless non-invasive methods of patient diagnosis and treatment. There are two principles behind this: greater patient comfort and lower cost. Tears, hair, saliva, urine, and faeces can replace blood for diagnosis. The varied constituents in these biological materials can serve as biomarkers for the detection of both local and systemic diseases. In this paper, we review a range of diagnostic techniques — all using biological material obtained via non-invasive procedure — for detecting medical conditions in pregnant women. PubMed, Medline, Embase, and the Cochrane Library were searched from January 1996 until December 2018. Forty seven studies were included: thirty-five original articles, nine reviews and three meta-analysis. Analysis showed that saliva, hair, tears, and other biological material — obtained via non-invasive methods — may serve as clinically informative biomarkers. These biomarkers may be used for: toxicology, psychological studies, disease detection, biomonitoring, and drug abuse. The analysis of tears, hair, saliva, urine, and faeces is a safe, noninvasive and useful diagnostic tool within groups of pregnant women, but further investigation is necessary to fully realize the promise of these novel diagnostic tools.

Abstract

As medical technology evolves, clinicians are increasingly choosing relatively painless non-invasive methods of patient diagnosis and treatment. There are two principles behind this: greater patient comfort and lower cost. Tears, hair, saliva, urine, and faeces can replace blood for diagnosis. The varied constituents in these biological materials can serve as biomarkers for the detection of both local and systemic diseases. In this paper, we review a range of diagnostic techniques — all using biological material obtained via non-invasive procedure — for detecting medical conditions in pregnant women. PubMed, Medline, Embase, and the Cochrane Library were searched from January 1996 until December 2018. Forty seven studies were included: thirty-five original articles, nine reviews and three meta-analysis. Analysis showed that saliva, hair, tears, and other biological material — obtained via non-invasive methods — may serve as clinically informative biomarkers. These biomarkers may be used for: toxicology, psychological studies, disease detection, biomonitoring, and drug abuse. The analysis of tears, hair, saliva, urine, and faeces is a safe, noninvasive and useful diagnostic tool within groups of pregnant women, but further investigation is necessary to fully realize the promise of these novel diagnostic tools.

Full Text:

View PDF Download PDF file Supp./Additional Files [1]
Get Citation

Keywords

tears; saliva; faeces; urine; hair; noninvasive

Supp./Additional Files (1)
Letter to the Editor
View
643KB
About this article
Title

Saliva, hair, tears, and other biological materials obtained non-invasively for diagnosis in pregnancy: a literature review

Journal

Ginekologia Polska

Issue

Vol 90, No 8 (2019)

Article type

Review paper

Pages

475-481

Published online

2019-08-30

Page views

1605

Article views/downloads

1410

DOI

10.5603/GP.2019.0082

Pubmed

31482552

Bibliographic record

Ginekol Pol 2019;90(8):475-481.

Keywords

tears
saliva
faeces
urine
hair
noninvasive

Authors

Aleksandra Zygula
Przemyslaw Kosinski
Miroslaw Wielgos

References (47)
  1. Jing J, Gao Y. Urine biomarkers in the early stages of diseases: current status and perspective. Discov Med. 2018; 25(136): 57–65.
    PubMed
  2. Bonaldo MC, Ribeiro IP, Lima NS, et al. Isolation of Infective Zika Virus from Urine and Saliva of Patients in Brazil. PLoS Negl Trop Dis. 2016; 10(6): e0004816.
    CrossRefPubMed
  3. Pomar L, Vouga M, Lambert V, et al. Maternal-fetal transmission and adverse perinatal outcomes in pregnant women infected with Zika virus: prospective cohort study in French Guiana. BMJ. 2018; 363: k4431.
    CrossRefPubMed
  4. Garovic VD. The role of the podocyte in preeclampsia. Clin J Am Soc Nephrol. 2014; 9(8): 1337–1340.
    CrossRefPubMed
  5. Aita K, Etoh M, Hamada H, et al. Acute and transient podocyte loss and proteinuria in preeclampsia. Nephron Clin Pract. 2009; 112(2): c65–c70.
    CrossRefPubMed
  6. Zhao S, Gu Y, Groome L, et al. OS062. Oxidative stress mediates podocyte injury in preeclampsia. Pregnancy Hypertension: An International Journal of Women's Cardiovascular Health. 2012; 2(3): 210–211.
    CrossRef
  7. Pozo OJ, Marcos J, Khymenets O, et al. SULFATION PATHWAYS: Alternate steroid sulfation pathways targeted by LC-MS/MS analysis of disulfates: application to prenatal diagnosis of steroid synthesis disorders. J Mol Endocrinol. 2018; 61(2): M1–M12.
    CrossRefPubMed
  8. Caughey AB, Hopkins LM, Norton ME. Chorionic villus sampling compared with amniocentesis and the difference in the rate of pregnancy loss. Obstet Gynecol. 2006; 108(3 Pt 1): 612–616.
    CrossRefPubMed
  9. Guo LW, Shackleton CH, Wilson WK. Synthesis of ring B unsaturated estriols. Confirming the structure of a diagnostic analyte for Smith-Lemli-Opitz syndrome. Org Lett. 2001; 3(16): 2547–2550.
    PubMed
  10. Jezela-Stanek A, Ciara E, Małunowicz E, et al. Smith-Lemli-Opitz syndrome Collaborative Group. Differences between predicted and established diagnoses of Smith-Lemli-Opitz syndrome in the Polish population: underdiagnosis or loss of affected fetuses? J Inherit Metab Dis. 2010; 33 Suppl 3: S241–S248.
    CrossRefPubMed
  11. Choden T, Mandaliya R, Charabaty A, et al. Monitoring inflammatory bowel disease during pregnancy: Current literature and future challenges. World J Gastrointest Pharmacol Ther. 2018; 9(1): 1–7.
    CrossRefPubMed
  12. Stephansson O, Larsson H, Pedersen L, et al. Crohn's disease is a risk factor for preterm birth. Clin Gastroenterol Hepatol. 2010; 8(6): 509–515.
    CrossRefPubMed
  13. Cappell MS, Colon VJ, Sidhom OA. A study at 10 medical centers of the safety and efficacy of 48 flexible sigmoidoscopies and 8 colonoscopies during pregnancy with follow-up of fetal outcome and with comparison to control groups. Dig Dis Sci. 1996; 41(12): 2353–2361.
    CrossRefPubMed
  14. Siddiqui I, Majid H, Abid S. Update on clinical and research application of fecal biomarkers for gastrointestinal diseases. World J Gastrointest Pharmacol Ther. 2017; 8(1): 39–46.
    CrossRefPubMed
  15. Julsgaard M. Fecal Calprotectin Is Not Affected by Pregnancy: Clinical Implications for the Management of Pregnant Patients with Inflammatory Bowel Disease. Inflamm Bowel Dis. 2017; 23(7): 1240–1246.
  16. Dai C, Jiang M, Sun MJ. Fecal markers in the management of inflammatory bowel disease. Postgrad Med. 2018; 130(7): 597–606.
    CrossRefPubMed
  17. Aass C, Norheim I, Eriksen EF, et al. Single unit filter-aided method for fast proteomic analysis of tear fluid. Anal Biochem. 2015; 480: 1–5.
    CrossRefPubMed
  18. Zhou L, Beuerman RW. Tear analysis in ocular surface diseases. Prog Retin Eye Res. 2012; 31(6): 527–550.
    CrossRefPubMed
  19. Kan S, Acar U, Kizilgul M, et al. Tear Film and Ocular Surface Evaluation in Gestational Diabetes Mellitus. Semin Ophthalmol. 2018; 33(3): 402–406.
    CrossRefPubMed
  20. Gutierrez HL, Hund L, Shrestha S, et al. Ethylglucuronide in maternal hair as a biomarker of prenatal alcohol exposure. Alcohol. 2015; 49(6): 617–623.
    CrossRefPubMed
  21. Jones TB, Bailey BA, Sokol RJ. Alcohol use in pregnancy: insights in screening and intervention for the clinician. Clin Obstet Gynecol. 2013; 56(1): 114–123.
    CrossRefPubMed
  22. Boscolo-Berto R, Favretto D, Cecchetto G, et al. Sensitivity and specificity of EtG in hair as a marker of chronic excessive drinking: pooled analysis of raw data and meta-analysis of diagnostic accuracy studies. Ther Drug Monit. 2014; 36(5): 560–575.
    CrossRefPubMed
  23. Mughal S, Siddiqui W. Depression, Postpartum. StatPearls, Treasure Island (FL) 2018.
  24. Stalder T, Kirschbaum C. Analysis of cortisol in hair--state of the art and future directions. Brain Behav Immun. 2012; 26(7): 1019–1029.
    CrossRefPubMed
  25. Caparros-Gonzalez RA, Romero-Gonzalez B, Strivens-Vilchez H, et al. Hair cortisol levels, psychological stress and psychopathological symptoms as predictors of postpartum depression. PLoS One. 2017; 12(8): e0182817.
    CrossRefPubMed
  26. Dunkel Schetter C, Tanner L. Anxiety, depression and stress in pregnancy: implications for mothers, children, research, and practice. Curr Opin Psychiatry. 2012; 25(2): 141–148.
    CrossRefPubMed
  27. Massey AJ, Campbell BK, Raine-Fenning N, et al. Relationship between hair and salivary cortisol and pregnancy in women undergoing IVF. Psychoneuroendocrinology. 2016; 74: 397–405.
    CrossRefPubMed
  28. Klevay LM, Christopherson DM, Shuler TR. Hair as a biopsy material: trace element data on one man over two decades. Eur J Clin Nutr. 2004; 58(10): 1359–1364.
    CrossRefPubMed
  29. Li Z, Huo W, Li Z, et al. Association between titanium and silver concentrations in maternal hair and risk of neural tube defects in offspring: A case-control study in north China. Reprod Toxicol. 2016; 66: 115–121.
    CrossRefPubMed
  30. Jin Xi, Tian X, Liu Z, et al. Maternal exposure to arsenic and cadmium and the risk of congenital heart defects in offspring. Reprod Toxicol. 2016; 59: 109–116.
    CrossRefPubMed
  31. Liu Z, Lin Y, Tian X, et al. Association between maternal aluminum exposure and the risk of congenital heart defects in offspring. Birth Defects Res A Clin Mol Teratol. 2016; 106(2): 95–103.
    CrossRefPubMed
  32. Chiandetti A, Hernandez G, Mercadal-Hally M, et al. Prevalence of prenatal exposure to substances of abuse: questionnaire versus biomarkers. Reprod Health. 2017; 14(1): 137.
    CrossRefPubMed
  33. Koss CA, Natureeba P, Mwesigwa J, et al. Hair concentrations of antiretrovirals predict viral suppression in HIV-infected pregnant and breastfeeding Ugandan women. AIDS. 2015; 29(7): 825–830.
    CrossRefPubMed
  34. Pink R, Simek J, Vondrakova J, et al. SALIVA AS A DIAGNOSTIC MEDIUM. Biomedical Papers. 2009; 153(2): 103–110.
    CrossRef
  35. Kaczor-Urbanowicz K, Carreras-Presas CM, Aro K, et al. Saliva diagnostics – Current views and directions. Exp Biol Med. 2016; 242(5): 459–472.
    CrossRef
  36. Georgiou HM, Di Quinzio MKW, Permezel M, et al. Predicting Preterm Labour: Current Status and Future Prospects. Dis Markers. 2015; 2015: 435014.
    CrossRefPubMed
  37. Priya B, Mustafa MD, Guleria K, et al. Salivary progesterone as a biochemical marker to predict early preterm birth in asymptomatic high-risk women. BJOG. 2013; 120(8): 1003–1011.
    CrossRefPubMed
  38. Castles A, Adams EK, Melvin CL, et al. Effects of smoking during pregnancy. Five meta-analyses. Am J Prev Med. 1999; 16(3): 208–215.
    PubMed
  39. Benowitz N, Dempsey D. Pharmacotherapy for smoking cessation during pregnancy. Nicotine Tob Res. 2004; 6 Suppl 2: S189–S202.
    CrossRefPubMed
  40. Windsor R, Woodby L, Miller T, et al. Effectiveness of Agency for Health Care Policy and Research clinical practice guideline and patient education methods for pregnant smokers in Medicaid maternity care. American Journal of Obstetrics and Gynecology. 2000; 182(1): 68–75.
    CrossRef
  41. Dietz PM, Homa D, England LJ, et al. Estimates of nondisclosure of cigarette smoking among pregnant and nonpregnant women of reproductive age in the United States. Am J Epidemiol. 2011; 173(3): 355–359.
    CrossRefPubMed
  42. Benowitz NL. Cotinine as a biomarker of environmental tobacco smoke exposure. Epidemiol Rev. 1996; 18(2): 188–204.
    CrossRefPubMed
  43. Polanska K, Krol A, Kaluzny P, et al. Estimation of Saliva Cotinine Cut-Off Points for Active and Passive Smoking during Pregnancy-Polish Mother and Child Cohort (REPRO_PL). Int J Environ Res Public Health. 2016; 13(12).
    CrossRefPubMed
  44. Shang M, Zhao J, Yang L, et al. Oxidative stress and antioxidant status in women with gestational diabetes mellitus diagnosed by IADPSG criteria. Diabetes Res Clin Pract. 2015; 109(2): 404–410.
    CrossRefPubMed
  45. Zygula A, Kosinski P, Zwierzchowska A, et al. Oxidative stress markers in saliva and plasma differ between diet-controlled and insulin-controlled gestational diabetes mellitus. Diabetes Res Clin Pract. 2019; 148: 72–80.
    CrossRefPubMed
  46. Łopucki M, Wawrzykowski J, Gęca T, et al. Preliminary analysis of the protein profile in saliva during physiological term and preterm delivery. Mol Med Rep. 2018; 17(6): 8253–8259.
    CrossRefPubMed
  47. Du Y, Zhang W, Wang ML. An On-Chip Disposable Salivary Glucose Sensor for Diabetes Control. J Diabetes Sci Technol. 2016; 10(6): 1344–1352.
    CrossRefPubMed

Regulations

Important: This website uses cookies. More >>

The cookies allow us to identify your computer and find out details about your last visit. They remembering whether you've visited the site before, so that you remain logged in - or to help us work out how many new website visitors we get each month. Most internet browsers accept cookies automatically, but you can change the settings of your browser to erase cookies or prevent automatic acceptance if you prefer.

By VM Media Group sp. z o.o., ul. Świętokrzyska 73, 80–180 Gdańsk
tel.:+48 58 320 94 94, faks:+48 58 320 94 60, e-mail:  viamedica@viamedica.pl